Proceedings 2003 VLDB Conference: 29th International Conference on Very Large Databases (VLDB)Morgan Kaufmann, 2003 M12 2 - 1050 pages Proceedings of the 29th Annual International Conference on Very Large Data Bases held in Berlin, Germany on September 9-12, 2003. Organized by the VLDB Endowment, VLDB is the premier international conference on database technology. |
From inside the book
Results 1-5 of 91
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... -Way Join Queries over Streaming Information Sources ................... 285 Stratis D. Viglas, Jeffrey F. Naughton, Josef Burger (University of Wisconsin-Madison, USA) Scheduling for shared window joins over data streams ...
... -Way Join Queries over Streaming Information Sources ................... 285 Stratis D. Viglas, Jeffrey F. Naughton, Josef Burger (University of Wisconsin-Madison, USA) Scheduling for shared window joins over data streams ...
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... Data Streams ..................................... 500 Lukasz Golab, M. Tamer Ozsu (University of Waterloo, Canada) Continuous K-Nearest Neighbor Queries for Continuously Moving Points with Updates ............................ 512 Glenn ...
... Data Streams ..................................... 500 Lukasz Golab, M. Tamer Ozsu (University of Waterloo, Canada) Continuous K-Nearest Neighbor Queries for Continuously Moving Points with Updates ............................ 512 Glenn ...
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... .... 826 Miaoyu Wang, Mitch Cherniack (Brandeis University, USA) Operator Scheduling in a Data Stream Manager ............................................................................................ 838 Don Carney, Ugur ...
... .... 826 Miaoyu Wang, Mitch Cherniack (Brandeis University, USA) Operator Scheduling in a Data Stream Manager ............................................................................................ 838 Don Carney, Ugur ...
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... Nathan Folkert, Abhinav Gupta, Lei Sheng, Sankar Subramanian (Oracle Corporation, USA) An Interpolated Volume Data Model ..................................................................................................
... Nathan Folkert, Abhinav Gupta, Lei Sheng, Sankar Subramanian (Oracle Corporation, USA) An Interpolated Volume Data Model ..................................................................................................
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... data item per bucket to capture linearly growing or shrinking frequencies at the expense of fewer buckets for a ... stream environment, static histograms are not an option at all, as there is no opportunity to store the incoming data or ...
... data item per bucket to capture linearly growing or shrinking frequencies at the expense of fewer buckets for a ... stream environment, static histograms are not an option at all, as there is no opportunity to store the incoming data or ...
Contents
17 | |
31 | |
Part 4 Industrial Sessions | 935 |
Part 5 Panels | 1041 |
Part 6 Demo Sessions | 1051 |
Author Index | 1153 |
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Common terms and phrases
ACM SIGMOD algorithm applications approach attribute average bisimulation bucket buffer cache misses clustering compressed compute Conf constraints contains context nodes corresponding cost Data Bubble data mining data set data stream database systems DBLP defined denote distance distributed edge efficient elements engine estimation evaluation example execution experiments Figure function global graph hash join hash table histograms ICDE implementation input integration interface join join algorithm load matching merge algorithm method micro-clusters MJoin operator optimization output PAC-Man Pagerank parameter partition path expression performance predicate probe problem Proc query optimization query plan query processing ranking relation repository retrieval rithm scalability scan schema Section selection semantics sequence server shows SIGMOD storage stored structure subtree techniques tion tree pattern tuples Unicode update VLDB Web.Views window workload XFDs XML document XML query XPath